Computational Fluid Dynamics Turbulence Model and Experimental Study for a Fontan Cavopulmonary Assist Device.

Head-flow HQ curves for a Fontan cavopulmonary assist device (CPAD) were measured using a blood surrogate in a mock circulatory loop and simulated with various computational fluid dynamics (CFD) models. The tests benchmarked the CFD tools for further enhancement of the CPAD design. Recommended Reynolds-Averaged Navier-Stokes (RANS) CFD approaches for the development of conventional ventricular assist devices (VAD) were found to have shortcomings when applied to the Fontan CPAD, which is designed to neutralize off-condition obstruction risks that could contribute to a major adverse event. The no-obstruction condition is achieved with a von Karman pump, utilizing large clearances and small blade heights, which challenge conventional VAD RANS-based CFD hemodynamic simulations. High-fidelity large eddy simulation (LES) is always recommended; however, this may be cost-inhibitive for optimization studies in commercial settings, thus the reliance on RANS models. This study compares head and power predictions of various RANS turbulence models, employing experimental measurements and LES results as a basis for comparison. The models include standard k-ϵ, re-normalization group k-ϵ, realizable k-ϵ, shear stress transport (SST) k-ω, SST with transitional turbulence, and Generalized k-ω. For the pressure head predictions, it was observed that the standard k-ϵ model provided far better agreement with experiment. For the rotor torque, k-ϵ predictions were 30% lower than LES, while the SST and LES torque values were near identical. For the Fontan CPAD, the findings support using LES for the final design simulations, k-ϵ model for head and general flow simulation, and SST for power, shear stress, hemolysis, and thrombogenicity predictions.

Crosslinked network microstructure of carbon nanomaterials promotes flaw-tolerant mechanical response.

Carbon nanomaterials, such as carbon nanotubes (CNTs) and carbon nanofibers (CNFs), are chemically inert in their highly graphitic forms. Various post processing methods can activate their surfaces to enhance their interactions with a host matrix in a nanocomposite. Chemical surface functionalization is used often. This method however can lead to major strength loss in nanomaterials stemming from induced surface defects (changing sp2 bonds to sp3 bonds). In this manuscript, we have experimentally studied the mechanical properties of the individual, pyrolysis-fabricated CNFs. These CNFs have a highly crosslinked 3D network of C-C bonds. The strength of CNFs has been studied as a function of O/C ratio. The loss in strength due to functionalization has been compared to that of other carbon nanomaterials with layered strcutures (CNT and graphene). Comparisons were also made with carbon microfibers. Fracture strength estimations of the critical flaw size in CNFs, CNTs and graphene were also made. The results revealed that despite having high surface area, carbon nanomaterials with crosslinked microstructure are resilient to flaws as big (deep) as 10-30 nm, while nanomaterials with layered structure (such as CNTs) experience a dramatic loss in strength with much lower flaw sizes. Hence, it seems that graphitic nanomaterials such as graphene and CNT have high strenght that, although higher than CNFs, comes at a cost to flaw tolerance and robustness. Since failure is often progressive, this work demonstrates a benefit that crosslinked nanomaterials have over highly graphitic ones, such as CNTs, in load bearing applications.